Modelling fatality curves of COVID-19 and the effectiveness of intervention strategies

Giovani L. Vasconcelos; Antônio M. S. Macêdo; Raydonal Ospina; Francisco A. G. Almeida; Gerson C. Duarte-Filho; Inês C. L. Souza

Because a large proportion of COVID-19 infections go undetected [18] , it is difficult to estimate the actual number of infected people within a given population. As many carriers of the virus are either asymptomatic or develop only mild symptoms, they will will not be detected unless they are tested. In other words, the number of confirmed cases for COVID-19 is a poor proxy for the total number of infections. Furthermore, the fraction of confirmed cases relative to the total number of infections depends heavily on the testing policy of each country, which makes it problematic to compare the evolution of confirmed cases among different countries. In contrast, the number of deaths attributed to COVID-19 is a much more reliable measure of the advance of the epidemics and its severity. Of course, many other factors, such as age structure of a population and quality of care, may affect the fraction of deaths relative to the number of confirmed cases. Nevertheless, it is expected that overall the evolution of number of deaths bear a relation to the dynamics of the number of infections [19] . Under these circumstances and in the absence of reliable estimates for the number of infected cases for COVID-19, we decided here to seek an alternative approach and model directly the mortality curves, defined as the cumulative number of deaths as a function of time, rather than the number of confirmed cases, as is more usually done.